Integrating thermodynamic constraints in metabolic flux balance analysis have had many applications in recent years. Although by introducing new thermodynamic constraints, directionalities can be assigned to the reactions and the solution space can be reduced significantly, we will still have some bidirectional reactions (BDRs) which in turn will result in alternative flux distributions. Theoretically, with n bidirectional reactions we can have 2n combinations of BDRs, which makes it difficult to analyze the network. However, the degrees of freedom of the network are less, since the activities of some reactions are coupled to the activities of others. Flux coupling analysis (FCA), defines different types of coupling relationships for a pair of fluxes: full coupling, partial coupling, and directional coupling. In the present work, we will introduce TFCA, Thermodynamics-based Flux Coupling Analysis, which applies FCA for thermodynamically constrained models. Based on the identified coupling relationships using TFCA, some BDR combinations are automatically removed. For instance, if the forward direction of reaction a is coupled to the forward direction of reaction b, one can easily see that the combination that contains forward direction of a and backward direction of b cannot happen. By applying TFCA on a reduced E. coli metabolic network model with several types of integrated constraints, we observed that coupling between reactions will reduce the number of possible BDR combinations from 27 to ~25. Reducing the number of possible directionality combinations can help in better studying the behavior of organism under observed physiology. In addition, we observed that some couplings between reactions are due to thermodynamic constraints and this introduces more dependencies between reactions. Another promising opportunity that TFCA offers is for pathway engineering to identify how to couple known and novel pathway(s) in order to improve the performance of whole-cell biocatalysts. We will use this approach for the analysis and design of the production of 3-hydroxypropanoate (3HP) and 1,4-butanediol (BDO), which are two of the most valuable organic compounds for biosynthesis.

Flux coupling analysis for studying the dependencies and degrees of freedom in thermodynamically constrained metabolic network models

253rd National Meeting (2017)

The official archive and repository for all ACS Meetings & Expositions abstracts and select posters or presentations.